International Workshop on GENOMIC SIGNAL PROCESSING AND STATISTICS ( GENSIPS )

نویسندگان

  • Gurinder Atwal
  • Ulisses Braga-Neto
  • Xiaodong Cai
  • Aniruddha Datta
  • Nevenka Dimitrova
  • Edward Dougherty
  • John Goutsias
  • Yu-fei Huang
  • Ivan Ivanov
  • Judith Klein-Seetharaman
  • Rui Kuang
  • Doheon Lee
  • Ranadip Pal
  • Xiaoning Qian
  • Dan Schonfeld
  • Chao Sima
  • Haris Vikalo
  • Xiaodong Wang
  • Byung-Jun Yoon
  • Michael Wigler
  • Boris Yamrom
  • Jud Kendell
  • Yoon-Ha Lee
  • Nick Navin
  • Kenny Ye
چکیده

s of papers presented at the 9th IEEE International Workshop on GENOMIC SIGNAL PROCESSING AND STATISTICS (GENSIPS) November 10–November 12, 2010 Cold Spring Harbor Laboratory Cold Spring Harbor, New York Abstracts of papers presented at the 9th IEEE International Workshop ons of papers presented at the 9th IEEE International Workshop on GENOMIC SIGNAL PROCESSING AND STATISTICS (GENSIPS) November 10–November 12, 2010

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منابع مشابه

2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSiPS 2013, Houston, TX, USA, November 17-19, 2013

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Digital Binary Phase-shift Keyed Signal Detector

We have developed the effective algorithm for detecting digital binary phase-shift keyed signals. This algorithm requires a small number of arithmetic operations over the signal period. It can be relatively easy implemented based on the modern programmable logic devices. It also provides high interference immunity by identifying signal presence when signal-to-noise ratio is much less that its w...

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Large scale features in DNA genomic signals

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A Novel Multi-user Detection Approach on Fluctuations of Autocorrelation Estimators in Non-Cooperative Communication

Recently, blind multi-user detection has become an important topic in code division multiple access (CDMA) systems. Direct-Sequence Spread Spectrum (DSSS) signals are well-known due to their low probability of detection, and secure communication. In this article, the problem of blind multi-user detection is studied in variable processing gain direct-sequence code division multiple access (VPG D...

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Independent component analysis and beyond

Independent component analysis (ICA) aims at extracting unknown hidden factors/components from multivariate data using only the assumption that the unknown factors are mutually independent. Since the introduction of ICA concepts in the early 1980s in the context of neural networks and array signal processing, many new successful algorithms have been proposed that are now well-established method...

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تاریخ انتشار 2010